EconPapers    
Economics at your fingertips  
 

Prediction in a spatial nested error components panel data model

Badi Baltagi () and Alain Pirotte

International Journal of Forecasting, 2014, vol. 30, issue 3, 407-414

Abstract: This paper derives the Best Linear Unbiased Predictor (BLUP) for a spatial nested error components panel data model. This predictor is useful for panel data applications that exhibit spatial dependence and a nested (hierarchical) structure. The predictor allows for unbalancedness in the number of observations in the nested groups. One application includes forecasting average housing prices located in a county nested in a state. When deriving the BLUP, we take into account the spatial correlation across counties, as well as the unbalancedness due to observing different numbers of counties nested in each state. Ignoring the nested spatial structure leads to inefficiency and inferior forecasts. Using Monte Carlo simulations, we show that our feasible predictor is better in root mean square error performance than the usual fixed and random effects panel predictors which ignore the spatial nested structure of the data.

Keywords: Spatial nested error components; Unbalanced panels; Forecasting; Linear predictor; BLUP (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207014000041
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:30:y:2014:i:3:p:407-414

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

 
Page updated 2019-07-30
Handle: RePEc:eee:intfor:v:30:y:2014:i:3:p:407-414